code: def test_categorical_dist_kl_div_batch():
      n_classes = 3
      dist_a = CategoricalDist(
          n_classes=n_classes,
          probs=mx.nd.array(
              [[0.4, 0.2, 0.4], [0.4, 0.2, 0.4], [0.4, 0.2, 0.4]]
          ),
      )
      dist_b = CategoricalDist(
          n_classes=n_classes,
          probs=mx.nd.array(
              [[0.3, 0.4, 0.3], [0.3, 0.4, 0.3], [0.3, 0.4, 0.3]]
          ),
      )
      actual = dist_a.kl_div(dist_b).asnumpy()
      np.testing.assert_almost_equal(
          actual=actual, desired=[0.09151624, 0.09151624, 0.09151624]
      )
  
imports: import mxnet
  import numpy
  import os
  import pytest
  from scipy import stats
  import sys
  from rl_coach.architectures.head_parameters import PPOHeadParameters
  from rl_coach.architectures.mxnet_components.heads.ppo_head import CategoricalDist, MultivariateNormalDist, DiscretePPOHead, ClippedPPOLossDiscrete, ClippedPPOLossContinuous, PPOHead
  from rl_coach.agents.clipped_ppo_agent import ClippedPPOAlgorithmParameters, ClippedPPOAgentParameters
  from rl_coach.spaces import SpacesDefinition, DiscreteActionSpace
label_desc: Use image node_id 11 for calling a global function with example usage: test_categorical_dist_kl_div_batch() without return types